U.S. patent application number 15/894695 was filed with the patent office on 2018-08-16 for nutrition scoring system.
This patent application is currently assigned to NUTRILYZE LLC. The applicant listed for this patent is NUTRILYZE LLC. Invention is credited to Joseph DUNN, Joseph T. WHITAKER.
Application Number | 20180233064 15/894695 |
Document ID | / |
Family ID | 63105345 |
Filed Date | 2018-08-16 |
United States Patent
Application |
20180233064 |
Kind Code |
A1 |
DUNN; Joseph ; et
al. |
August 16, 2018 |
NUTRITION SCORING SYSTEM
Abstract
Method for determining a personalized nutrition score for a
given meal for a particular user. Traditionally, users choose meals
in an ad-hoc fashion, based on dimly remembered guidance aimed at
an average person. However, dietary needs vary greatly from
person-to-person, based on age, sex, weight, activity level,
weight-loss goals, genetics, and many other factors. Furthermore,
published nutritional information for meals or individual foods are
also based on average portion and serving sizes, and may not
accurately reflect the amount consumed by a user. Thus, embodiments
of the invention evaluate a potential meal for a user and determine
a score representing the nutritional benefits of that meal for the
particular user.
Inventors: |
DUNN; Joseph; (Kansas City,
MO) ; WHITAKER; Joseph T.; (Napa, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
NUTRILYZE LLC |
Kansas City |
MO |
US |
|
|
Assignee: |
NUTRILYZE LLC
|
Family ID: |
63105345 |
Appl. No.: |
15/894695 |
Filed: |
February 12, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62458128 |
Feb 13, 2017 |
|
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|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/9535 20190101;
G06F 16/24578 20190101; G09B 19/0092 20130101 |
International
Class: |
G09B 19/00 20060101
G09B019/00; G06F 17/30 20060101 G06F017/30 |
Claims
1. A method of determining a user-specific nutrition score for a
meal, comprising the steps of: determining a plurality of baseline
recommended intake values for a plurality of nutrients, wherein the
plurality of nutrients includes a plurality of macronutrients and a
plurality of micronutrients; adjusting the plurality of baseline
recommended intake values based on demographic information for the
user to obtain a respective plurality of custom recommended intake
values; further adjusting the plurality of custom recommended
intake values based on biometric data for the user to obtain a
respective plurality of dynamic recommended intake values; wherein
the biometric data is obtained from a peripheral device;
determining, for a potential meal, nutrient content values for at
least a portion of the plurality of nutrients; calculating, based
on the plurality of nutrient content values, the plurality of
dynamic recommended intake values, and the condition of the user a
macronutrient sufficiency score, a micronutrient sufficiency score,
and a detriment score; and calculating a meal score based at least
in part on the macronutrient sufficiency score, the micronutrient
sufficiency score, and the detriment score.
2. The method of claim 1, wherein the peripheral device is one of a
health condition monitor or an activity tracker.
3. The method of claim 2, wherein the activity tracker is at least
one of a wearable device or an exercise machine.
4. The method of claim 2, wherein the health condition monitor is
at least one of a glucose monitor, heart monitor, or blood pressure
monitor.
5. The method of claim 1, wherein the potential meal is selected
from a plurality of potential meals from an online database.
6. The method of claim 1, wherein the potential meal is selected
from a plurality of potential meals or ingredients provided by a
smart appliance.
7. The method of claim 1, wherein the meal score is further based
at least in part on user preferences.
8. The method of claim 1, wherein the macronutrient sufficiency
score, the micronutrient sufficiency score, and the detriment score
are based at least in part on expected future activity of the
user.
9. The method of claim 1, wherein information associated with the
potential meal is received from a peripheral device, and wherein
the information associated with the potential meal is an image of
the potential meal.
10. A system for determining a user-specific nutrition score for a
meal, comprising: a data store storing a plurality of baseline
recommended intake values for a plurality of nutrients, wherein the
plurality of nutrients includes a plurality of macronutrients and a
plurality of micronutrients; a processor; a first peripheral device
configured to gather biometric data from the user; a second
peripheral device configured to gather information associated with
a potential meal; one or more non-transitory computer-readable
media storing computer-executable instructions that, when executed,
perform the method of determining a user-specific nutrition score
for a meal, the method comprising: adjusting the plurality of
baseline recommended intake values based on demographic information
for the user to obtain a respective plurality of custom recommended
intake values; further adjusting the plurality of custom
recommended intake values based on the biometric data from the user
to obtain a respective plurality of dynamic recommended intake
values; determining nutrient content values for at least a portion
of the plurality of nutrients in the potential meal; storing the
determined nutrient content values in the data store; calculating,
based at least in part on the plurality of nutrient content values,
the plurality of dynamic recommended intake values, and the
biometric data, a macronutrient sufficiency score, a micronutrient
sufficiency score, and a detriment score; and calculating a total
score based at least in part on the macronutrient sufficiency
score, the micronutrient sufficiency score, and the detriment
score.
11. The system of claim 10, wherein the second peripheral device is
a mobile device and the information associated with the potential
meal is on online menu.
12. The system of claim 10, wherein the information associated with
the potential meal is an image of the potential meal.
13. The system of claim 10, wherein the potential meal is one of a
plurality of potential meals, and wherein the processor calculates
scores for the plurality of potential meals.
14. The system of claim 13, wherein the second peripheral device is
a mobile device and the plurality of potential meals are received
from an online menu associated with the GPS location of the mobile
device.
15. The system of claim 14, wherein at least one of the potential
meals is recommended to the user via a graphical user interface
generated by the processor.
16. The system of claim 10, wherein the first peripheral device is
one of an activity tracker or a health monitor.
17. One or more computer-readable media storing computer-executable
instructions which, when executed by a computer perform a method of
determining a user-specific nutrition score for a meal, the method
comprising the steps of: determining a plurality of baseline
recommended intake values for a plurality of nutrients, wherein the
plurality of nutrients includes a plurality of macronutrients and a
plurality of micronutrients; adjusting the plurality of baseline
recommended intake values based on demographic information for the
user to obtain a respective plurality of custom recommended intake
values; further adjusting the plurality of custom recommended
intake values based on biometric data for the user to obtain a
respective plurality of dynamic recommended intake values, wherein
the biometric data is received from a peripheral device; receiving
information associated with a potential meal; determining, for the
potential meal, using the information associated with the potential
meal, nutrient content values for at least a portion of the
plurality of nutrients; calculating, based at least in part on the
plurality of nutrient content values, the plurality of dynamic
recommended intake values, and the biometric data, a macronutrient
sufficiency score, a micronutrient sufficiency score, and a
detriment score; calculating a total score based at least in part
on the macronutrient sufficiency score, the micronutrient
sufficiency score, and the detriment score; and recommending the
potential meal to the user via a graphical user interface.
18. The media of claim 17, wherein the information associated with
the potential meal is an image of the potential meal and received
from a peripheral device.
19. The media of claim 18, wherein the peripheral device is a
mobile phone and the information associated with the potential meal
is a menu associated with the GPS location of the mobile phone.
20. The media of claim 17, wherein the peripheral device is one of
a health condition monitor or an activity tracker.
Description
RELATED APPLICATIONS
[0001] This non-provisional patent application claims priority
benefit, with regard to all common subject matter, of earlier-filed
U.S. Provisional Patent Application No. 62/458,128 filed Feb. 13,
2017 and entitled NUTRITION SCORING SYSTEM. The identified
earlier-filed provisional patent application is hereby incorporated
by reference in its entirety into the present application.
BACKGROUND
1. Field
[0002] Embodiments of the invention generally relate to nutrition
science and, more particularly, to a system for evaluating a
potential meal for a user and determining a score representing the
nutritional benefits of that meal for the particular user.
2. Related Art
[0003] Traditionally, users choose meals in an ad-hoc fashion,
based on dimly remembered guidance aimed at an average person.
However, dietary needs vary greatly from one person to another,
based on factors such as age, sex, weight, activity level,
weight-loss goals, eating habits, dietary restrictions, dietary
preferences, genetics, and many other factors. Furthermore,
published nutritional information for meals or individual foods are
also based on average portion and serving sizes and may not
accurately reflect the amount consumed by a user. Finally,
potential meals that are beneficial in one nutritional aspect (for
example, high in vitamins) may be harmful in another nutritional
aspect (for example, high in saturated fats). As such, there is a
need for a system that can automatically analyze a potential meal
along a number of axes and calculate a single, easily
comprehensible score for the potential meal for the particular
user.
SUMMARY
[0004] Embodiments of the invention address the above-described
need by providing for a system that automatically determines a
user's nutritional needs and scores meals based on their
nutritional content as compared to the user's needs.
[0005] In particular, in a first embodiment, the invention includes
a method of determining a user-specific nutrition score for a meal,
comprising the steps of determining a plurality of baseline
recommended intake values for a plurality of nutrients, wherein the
plurality of nutrients includes a plurality of macronutrients and a
plurality of micronutrients, adjusting the plurality of baseline
recommended intake values based on demographic information for the
user to obtain a respective plurality of custom recommended intake
values, further adjusting the plurality of custom recommended
intake values based on biometric data for the user to obtain a
respective plurality of dynamic recommended intake values, wherein
the biometric data is obtained from a peripheral device;
determining, for a potential meal, nutrient content values for at
least a portion of the plurality of nutrients, calculating, based
on the plurality of nutrient content values and the plurality of
dynamic recommended intake values, a macronutrient sufficiency
score, a micronutrient sufficiency score, and a detriment score,
and calculating a meal score based at least in part on the
macronutrient sufficiency score, the micronutrient sufficiency
score, and the detriment score.
[0006] In a second embodiment, the invention includes a system for
determining a user-specific nutrition score for a meal, comprising
the steps of determining a plurality of baseline recommended intake
values for a plurality of nutrients, wherein the plurality of
nutrients includes a plurality of macronutrients and a plurality of
micronutrients, adjusting the plurality of baseline recommended
intake values based on demographic information for the user to
obtain a respective plurality of custom recommended intake values,
further adjusting the plurality of custom recommended intake values
based on biometric data for the user to obtain a respective
plurality of dynamic recommended intake values, wherein the
biometric data is received from a first peripheral device
associated with the user, receiving information associated with a
potential meal, wherein the information associated with the
potential meal is based at least in part on information received
from a second peripheral device, determining, for a potential meal,
nutrient content values for at least a portion of the plurality of
nutrients, calculating, based on the plurality of nutrient content
values and the plurality of dynamic recommended intake values, a
macronutrient sufficiency score, a micronutrient sufficiency score,
and a detriment score, and calculating a meal score based at least
in part on the macronutrient sufficiency score, the micronutrient
sufficiency score, and the detriment score.
[0007] In a third embodiment, the invention includes one or more
computer-readable media storing computer-executable instructions,
when executed by a computer perform a method of determining a
user-specific nutrition score for a meal, the method comprising the
steps of determining a plurality of baseline recommended intake
values for a plurality of nutrients, wherein the plurality of
nutrients includes a plurality of macronutrients and a plurality of
micronutrients, adjusting the plurality of baseline recommended
intake values based on demographic information for the user to
obtain a respective plurality of custom recommended intake values,
further adjusting the plurality of custom recommended intake values
based on biometric data for the user to obtain a respective
plurality of dynamic recommended intake values, wherein the
biometric data is received from a peripheral device, receiving
information associated with a potential meal, determining, for a
potential meal, using the information associated with the potential
meal, nutrient content values for at least a portion of the
plurality of nutrients, calculating, based on the plurality of
nutrient content values and the plurality of dynamic recommended
intake values, a macronutrient sufficiency score, a micronutrient
sufficiency score, and a detriment score, and calculating a meal
score based at least in part on the macronutrient sufficiency
score, the micronutrient sufficiency score, and the detriment
score.
[0008] This summary is provided to introduce a selection of
concepts in a simplified form that are further described below in
the detailed description. This summary is not intended to identify
key features or essential features of the claimed subject matter,
nor is it intended to be used to limit the scope of the claimed
subject matter. Other aspects and advantages of the current
invention will be apparent from the following detailed description
of the embodiments and the accompanying drawing figures.
BRIEF DESCRIPTION OF THE DRAWING FIGURES
[0009] Embodiments of the invention are described in detail below
with reference to the attached drawing figures, wherein:
[0010] FIG. 1 depicts an exemplary hardware platform for certain
embodiments of the invention;
[0011] FIG. 2 depicts an exemplary nutrient chart;
[0012] FIG. 3 depicts an exemplary graphical user interface
presenting a user profile in embodiments of the invention;
[0013] FIG. 4 depicts an exemplary embodiment of a meal ingredient
list;
[0014] FIG. 5 depicts exemplary nutrient and detriment scoring
table presented on a graphical user interface in embodiments of the
invention;
[0015] FIG. 6 depicts an exemplary meal imaging in embodiments of
the invention;
[0016] FIG. 7 depicts an exemplary graphical user interface in
embodiments of the invention;
[0017] FIG. 8 depicts an exemplary nutrients breakdown list
presented on a graphical user interface in embodiments of the
invention;
[0018] FIG. 9 depicts the exemplary nutrients breakdown of the
embodiment depicted in FIG. 8;
[0019] FIG. 10 depicts an exemplary online meal ordering service
accessible through a graphical user interface in embodiments of the
invention;
[0020] FIG. 11 depicts exemplary devices and appliances associated
with embodiments of the invention;
[0021] FIG. 12 depicts an exemplary graphical user interface
accessing devices and appliances in embodiments of the
invention;
[0022] FIG. 13 depicts an exemplary graphical user interface
presenting meal options in embodiments of the invention;
[0023] FIG. 14 depicts an exemplary graphical user interface
presenting nutrient and detriment information for a meal in
embodiments of the invention;
[0024] FIG. 15 depicts a flowchart illustrating the operation of a
method in accordance with an embodiment of the invention; and
[0025] The drawing figures do not limit the invention to the
specific embodiments disclosed and described herein. The drawings
are not necessarily to scale, emphasis instead being placed upon
clearly illustrating the principles of the invention.
DETAILED DESCRIPTION
[0026] At a high level, embodiments of the invention determine
dynamically adjusted recommended intake values for various
nutrients for a particular user based on a variety of demographic
and biometric data for that user and then score potential meals
based on their nutritional content as compared to the recommended
intake values for those nutrients. By presenting simple metrics in
an easily comprehensible form, the system makes it easier for users
to make good nutrition decisions.
[0027] The subject matter of embodiments of the invention is
described in detail below to meet statutory requirements; however,
the description itself is not intended to limit the scope of
claims. Rather, the claimed subject matter might be embodied in
other ways to include different steps or combinations of steps
similar to the ones described in this document, in conjunction with
other present or future technologies. Minor variations from the
description below will be obvious to one skilled in the art, and
are intended to be captured within the scope of the claimed
invention. Terms should not be interpreted as implying any
particular ordering of various steps described unless the order of
individual steps is explicitly described.
[0028] The following detailed description of embodiments of the
invention references the accompanying drawings that illustrate
specific embodiments in which the invention can be practiced. The
embodiments are intended to describe aspects of the invention in
sufficient detail to enable those skilled in the art to practice
the invention. Other embodiments can be utilized and changes can be
made without departing from the scope of the invention. The
following detailed description is, therefore, not to be taken in a
limiting sense. The scope of embodiments of the invention is
defined only by the appended claims, along with the full scope of
equivalents to which such claims are entitled.
[0029] In this description, references to "one embodiment," "an
embodiment," or "embodiments" mean that the feature or features
being referred to are included in at least one embodiment of the
technology. Separate reference to "one embodiment" "an embodiment",
or "embodiments" in this description do not necessarily refer to
the same embodiment and are also not mutually exclusive unless so
stated and/or except as will be readily apparent to those skilled
in the art from the description. For example, a feature, structure,
or act described in one embodiment may also be included in other
embodiments, but is not necessarily included. Thus, the technology
can include a variety of combinations and/or integrations of the
embodiments described herein.
[0030] Turning first to FIG. 1, an exemplary hardware platform for
certain embodiments of the invention is depicted. Computer 102 can
be a desktop computer, a laptop computer, a server computer, smart
exercise equipment or home appliances, a mobile device such as a
smartphone or tablet, or any other form factor of general- or
special-purpose computing device. Depicted with computer 102 are
several components, for illustrative purposes. In some embodiments,
certain components may be arranged differently or absent.
Additional components may also be present. Included in computer 102
is system bus 104, whereby other components of computer 102 can
communicate with each other. In certain embodiments, there may be
multiple busses or components may communicate with each other
directly. Connected to system bus 104 is central processing unit
(CPU) 106. Also attached to system bus 104 are one or more
random-access memory (RAM) modules 108. Also attached to system bus
104 is graphics card 110. In some embodiments, graphics card 104
may not be a physically separate card, but rather may be integrated
into the motherboard or the CPU 106. In some embodiments, graphics
card 110 has a separate graphics-processing unit (GPU) 112, which
can be used for graphics processing or for general purpose
computing (GPGPU). Also on graphics card 110 is GPU memory 114.
Connected (directly or indirectly) to graphics card 110 is display
116 for user interaction. In some embodiments no display is
present, while in others it is integrated into computer 102.
Similarly, peripherals such as keyboard 118 and mouse 120 are
connected to system bus 104. Like display 116, these peripherals
may be integrated into computer 102 or absent. Also connected to
system bus 104 is local storage 122, which may be any form of
computer-readable media, and may be internally installed in
computer 102 or externally and removeably attached.
[0031] Computer-readable media include both volatile and
nonvolatile media, removable and non removable media, and
contemplate media readable by a database. For example,
computer-readable media include (but are not limited to) RAM, ROM,
EEPROM, flash memory or other memory technology, CD-ROM, digital
versatile discs (DVD), holographic media or other optical disc
storage, magnetic cassettes, magnetic tape, magnetic disk storage,
and other magnetic storage devices. These technologies can store
data temporarily or permanently. However, unless explicitly
specified otherwise, the term "computer-readable media" should not
be construed to include physical, but transitory, forms of signal
transmission such as radio broadcasts, electrical signals through a
wire, or light pulses through a fiber-optic cable. Examples of
stored information include computer-usable instructions, data
structures, program modules, and other data representations.
[0032] Finally, network interface card (NIC) 124 is also attached
to system bus 104 and allows computer 102 to communicate over a
network such as network 126. NIC 124 can be any form of network
interface known in the art, such as Ethernet, ATM, fiber,
Bluetooth, or Wi-Fi (i.e., the IEEE 802.11 family of standards).
NIC 124 connects computer 102 to local network 126, which may also
include one or more other computers, such as computer 128, and
network storage, such as data store 130. Generally, a data store
such as data store 130 may be any repository from which information
can be stored and retrieved as needed. Examples of data stores
include relational or object oriented databases, spreadsheets, file
systems, flat files, directory services such as LDAP and Active
Directory, or email storage systems. A data store may be accessible
via a complex API (such as, for example, Structured Query
Language), a simple API providing only read, write and seek
operations, or any level of complexity in between. Some data stores
may additionally provide management functions for data sets stored
therein such as backup or versioning. Data stores can be local to a
single computer such as computer 128, accessible on a local network
such as local network 126, or remotely accessible over Internet
132. Local network 126 is in turn connected to Internet 132, which
connects many networks such as local network 126, remote network
134 or directly attached computers such as computer 136. In some
embodiments, computer 102 can itself be directly connected to
Internet 132.
[0033] Embodiments of the invention may score meals, snacks, or any
food based on nutritional value customized for a particular user.
Create a customized meal-plan for a user may begin by creating a
baseline nutrient profile. Broadly speaking, a nutrient profile
includes target values for a plurality of nutrients. As it is used
herein, the term "nutrient" includes any component of food that is
absorbed or otherwise metabolized by a person who eats it. For
example, nutrients include macronutrients (carbohydrates, protein,
and fats), micronutrients (vitamins and minerals), water, amino
acids, and dietary fiber. Nutrients may also be categorized
hierarchically. For example, alpha-linoleic acid is one type of
omega-3 fatty acid, which is in turn one type of unsaturated fat,
which is one type of fat, which is in turn one type of caloric
source. Thus, a dietary source of alpha-linoleic acid would count
toward the target values for all nutrients above it in the
hierarchy.
[0034] Target values may be determined from a variety of sources.
For example, the United States Food and Drug Administration
provides daily reference values for a variety of nutrients 202, as
shown in the exemplary table 200 in FIG. 2. Target values for a
nutrient 202 may be any constraint on the amount of the nutrient
202 that should be consumed. In embodiments, target values may be
daily values 204 or daily recommended values. For example, the
target values for vitamin B2 (Riboflavin) 206 may be 1.7
milligrams. Some nutrients 202 may have a maximum target value. For
example, the target value for sodium 208 may be 2,400 milligrams.
However, the target value may be assigned as a minimum of 2,300
milligrams depending on the source for the baseline nutrient
profile 200. Some such nutrients 202 (such as trans fats or added
sugars) may have a target value of zero, meaning that it is
desirable to consume as little of that nutrient 202 as possible.
Many nutrients 202 will have both an upper target value and a lower
target value. For example, the target value for caloric sources may
be between 2,400 and 2,600 calories. The type of target values may
differ between levels in the nutrient hierarchy. For example, the
target value for total fat 210 may be "between 50 and 70 grams
total, no more than 20 grams of which should be saturated fats
212." In some embodiments, target values are expressed on a daily
basis. In other embodiments, target values are apportioned
throughout the day. For example, the total target value for vitamin
A 214 might be "5,000 International Units (IU) daily," but (due to
the limited rate at which vitamin A 214 can be absorbed) this might
be broken down to "1,000 IU at breakfast, 2,000 IU at lunch, and
2,000 IU at dinner." The baseline nutrient profile 200 may be a
starting point for any user and may later be altered or customized
based on user input, demographic shifts, medical studies, or any
other information that may be relevant. Broadly speaking, target
values are broadly applicable across all life stage groups, and may
be adjusted, supplemented, or replaced based on user demographic
data, as described below.
[0035] Continuing with the exemplary embodiment depicted in FIG. 2,
once the baseline nutrient profile 200 for the user has been
constructed, the baseline nutrient profile 200 may be adjusted
based on user demographic data to create a custom user profile. The
daily values 204 given in FIG. 2 provide normative values for an
average person based on a daily caloric intake of 2,000 calories.
As such, when calculating the target value for these nutrients 202,
the daily values 204 may be scaled based on the target value for
total caloric intake calculated for the user. The baseline nutrient
profile 200 is exemplary only and the reference daily values 204
may also be derived from other sources. For example, the American
Heart Organization and the American Medical Association also
publish diet recommendations that may be used to supplement or
replace the FDA's guidelines given above.
[0036] As described above, target values for each nutrient 202 may
vary from user to user based on a wide variety of other factors.
For example, total recommended caloric intake could vary based on
the user's age, sex, current weight, weight-loss goals, activity
levels, and genetic profile or weighted against a demographic mean.
Other factors may also contribute to determine the target value for
nutrients 202. For example, folic acid (vitamin B9) 216 may have a
target value of "at least 400 micrograms" for most adults, but "at
least 600 micrograms" for women who are pregnant or plan to become
pregnant. Broadly, target values for each nutrient 202 may be
adjusted based on any demographic attribute or combination of
demographic attributes for the user. For example, if the user has a
genetic condition that causes vitamin B12 218 to be absorbed
inefficiently, then the target value for vitamin B12 218 can be
increased accordingly.
[0037] In some embodiments, the daily values 202 from the baseline
profile 200 may be replaced with values more specific to the
individual. For example, the daily value 204 given above for
Vitamin C 220 (across all life stage groups) is 60 mg. However,
some or all nutrients 202 may be assigned either an Estimated
Average Requirement (EAR) and Recommended Daily Allowance (RDA) or
an Adequate Intake (Al) value for each life stage. Broadly
speaking, the EAR and RDA are, respectively, essentially the median
and 97.5th percentile, of the distribution of deficiency
likelihoods for a given nutrient 202 and given life stage group.
The Al is a single threshold value for a particular life stage
group. Thus, in the example given above of Vitamin C 220, for men
31-50 years of age, the vitamin C EAR is 75 mg and the RDA is 90
mg, meaning 50% of men show signs of vitamin C deficiency when they
consume an average of 75 mg of vitamin C 220 daily, and only 2.5%
show signs of deficiency when consuming 90 mg per day on average.
As such, in some embodiments of the invention, the target value may
be calculated based on the RDA and EAR where it is available,
falling back to the Al threshold if no RDA and EAR are available,
with the DV as a final fallback if no more specific values are
available. These amounts may still further be personalized to an
individual user. For example, if the user has a genetic condition
(as indicated by a DNA analysis or other test) that causes certain
nutrients to be absorbed poorly, the target value may be increased
to reflect this. Similarly, an analysis of the user's microbiome
may indicate that certain foods or macronutrients are adsorbed more
or less readily, and the contribution by those foods towards the
target value can be adjusted accordingly.
[0038] One of skill in the art will appreciate that embodiments of
the invention are not comparing the amount of nutrients 202 in a
meal with a single target value to determine whether the user will
be deficient in that nutrient 202 if they eat that meal, but rather
examining the likelihood of deficiency if the user regularly
consumes meals with the same density of that nutrient 202.
[0039] In an embodiment depicting an exemplary graphical user
interface (GUI) 300 of the invention in FIG. 3, a user 302 Victoria
Bauer may create a user profile 304. The user 302 may log onto a
computer, smart phone, tablet, or any other device that may access
the internet and support the GUI 300. The user 302 may answer
questions related to demographic, medical history, family medical
history, genetics, and any other information that may assist in
determining a goal oriented, or health oriented, diet for user 302.
The user 302 may answer questions or provide information necessary
to create the user profile 304 that will enable the user access to,
and the system to create the baseline profile and adjustments and
customizations as described above.
[0040] The information provided by the user 302 in the user profile
304 may be listed under the account information header 306. The
system may store user 302 demographic information such as birthday
308, gender 310, height 312, and weight 314. The system may also
use activity data 316, goal oriented data 318, and food intake data
320. Medical information 322 may also be provided. For example, the
user 302 is 0-6 months postpartum and has type 2 diabetes. This
information may be necessary in providing a nutrient plan 324, or
recommended daily nutrition plan, that meets the goal oriented data
318 of the user 302 but keeps glucose levels within a safe range
based on the medical information 322. The nutrient plan 324 may
also incorporate snacks and timing to regulate glucose while
maintaining the goal oriented data 318, weight loss plan. For
example, the nutrient plan 324 may incorporate a good mixture of
protein, fat, and fiber. The user 302 may have an afternoon snack
of yogurt and an evening snack of cranberries. These specific
snacks may be built into the scoring with the understanding that
these snacks may be necessary based on the dynamic condition of the
user 302.
[0041] Though the nutrient plan 324 described above is tailored
towards managing type 2 diabetes, a Person of skill in the art will
appreciate that the plan may take into account many other types of
medical conditions and the system may connect to many types of
peripheral devices. For example, the user 302 may be allergic to
tree nuts so no food containing tree nuts or any other known
allergens are recommended by the system. The system may go a step
further in detecting known allergens and connect to a peripheral
device such as a allergen testing kit that may detect small amounts
of allergens that may be harmful to the user 302. The system may
warn the user 302 if such allergens are contained in the food thus
avoiding possible allergic reactions. The system may connect to
microbiome testing equipment and adjust the nutrient scores of the
nutrient plan 324 based on the immediate results for illnesses and
diseases such as inflammatory bowel disease, irritable bowel
syndrome, ulcerative colitis, and Crohn's disease. The system may
be capable of connecting to any peripheral hardware or software and
adjusting the nutrient plan 324 based on the information gathered.
The information may also be input manually by the user 302 or a
medical professional through any computer, phone, watch, or any
other device capable of receiving the manual input and storing a
database or connecting to the system.
[0042] The user profile 304 also presents the nutrition plan 324 as
recommended daily nutrition values 326. The nutrition plan 324 may
be based on the account information of the user 302; specifically,
the demographic, goal, and medical information. The nutrition plan
324, in the exemplary embodiment depicted in the user profile 304
in FIG. 3, presents the recommended daily nutrition values 326 and
calls for 1,700 calories, 90 grams of protein, 60 grams or fats,
and 200 grams of carbohydrates. The recommended daily nutrition
values 326 may be based on the account information and may be
updated or adjusted dynamically. The recommended daily nutrition
values 326 may be met by supplying the nutrients 202 across the
user preferred intake method. The user 302 preference is 3 daily
meals and 2 daily snacks as seen in the food intake data 320. The
preferred intake may also be decided by a medical practitioner or
the system may learn and automatically update to provide the best
results. The nutrition plan 324 may be a daily, weekly, or monthly
plan and may be determined by the user 302 health information 322
and goal oriented data 318.
[0043] Though in the embodiment depicted in FIG. 3 the desired goal
data 318 is described as weight loss, the user may input more
specific goals. For example, the user may be on a particular diet.
Many varieties of diet include limiting carbohydrates, fats,
calories or any other nutrients. Some diets include increasing
protein, vitamins and minerals, or any other nutrients. Some diets
are time sensitive and require certain nutrients or foods for 10,
20, 30, or any number of days. These diets may be manually entered
or may be accessed online and the system may include and adapt to
any diet that may be chosen by the user 302.
[0044] Once the user profile 304 is created and the recommended
daily nutrition values 204 are known, meals may be scored relative
to the daily nutrition plan 324. In embodiments, as depicted in
FIG. 4, the ingredients for a meal may be entered into the system
via the exemplary GUI 400 for evaluation and scoring. The
ingredients 402 may be entered manually, a meal may be imaged,
ingredient information may be retrieved online, or any other method
of the system receiving information about a food may be used.
Manually entering the ingredients 402 may be useful when following
a recipe or creating a meal. For example, if the meal is pancakes
404, then the user may indicate that the recipe includes 3 cups 406
of flour 408, 2 cups 410 of milk 412, 2 tablespoons 414 of sugar
416, and so on. The information for each nutrient 202 in each
ingredient 402 can be retrieved, scaled for the recipe and added to
the total for the recipe. Nutrition information for individual
ingredients 402 can be stored in the food database or retrieved
from an online database such as that provided by the United States
Department of Agriculture. Thus, for example, it might be
determined that the flour 408 has 96 grams of carbohydrates, 13
grams of protein, and 1.2 grams of fat per cup, milk 412 has 12
grams of carbohydrates, 8 grams of protein, and 2.4 grams of fat
per cup, and sugar has 12.6 grams of carbohydrates per tablespoon.
This information (and the information for all other nutrients and
ingredients 402 that may be present in pancakes 404) can be scaled
and added to determine that the pancakes 404 have a total 418 of
337 grams of carbohydrates, 55 grams of protein, and 8.4 grams of
fat per batch, and so on for each nutrient 202.
[0045] Continuing the example of pancakes 404 from above, the
potential meal might include two of the sixteen pancakes produced
by the recipe above, two strips of bacon (with 0.1 grams of
carbohydrates, 3 grams of protein, and 3.3 grams of fat each), and
12 oz. of milk. The aggregate nutrient information for the
potential meal would then be 60 g of carbohydrates, 25 grams of
protein, and 11.25 grams of fat. In some embodiments, meals can be
automatically scaled based on portion size information provided by
a smart plate. For example, the weight of a portion can be
determined and used to scale the portion. Though a smart plate is
used in this exemplary embodiment a smart fork, spoon, bowl,
measuring device, or any other appliance, or utensil that may
record, retrieve, or send information indicative of the amount of
an ingredient or meal may be used. One of skill in the art will
appreciate that, while the above example has been described with
reference to macronutrients, the same procedure can be followed for
all of the nutrients including micronutrients (vitamins and
minerals) to be considered by the system. Similarly, samples of
prepared foods can be analyzed with a nutrient test kit to
determine macronutrient and micronutrient information.
[0046] Turning to an exemplary GUI 500 in embodiments of the
invention depicted in FIG. 5, once the aggregate nutrient
information has been determined for each meal, the meal can be
scored. The macronutrient sufficiency score 502 may be calculated.
In some embodiments, subscores are first generated for each
nutrient. For example, in the embodiment depicted in FIG. 5,
assuming the target value for protein 504 for the user is "at least
50 grams," the target value for carbohydrates 506 is "at least 300
grams" and the total value for fat 508 is "between 50 and 70 grams"
then the breakfast described above would receive a protein 504
sufficiency score of 50%, a carbohydrate 506 sufficiency score of
20%, and a fat 508 sufficiency score of 22.5%. These values can
then be blended (for example, averaged) to determine a total
macronutrient sufficiency score 510 of 30.8%, if the average is
used. Although the example above scales the various nutrients
linearly, one of skill in the art will appreciate that this may not
be the case; rather, it may be a more sophisticated calculation
based on deficiency distribution or even deficiency distributions
with modifications based on supplementary research. Or more
sophisticated yet, the scores may be based on deficiency
distributions, user 302 preferences, daily, weekly, or monthly
activity including expected activity to preemptively provide
necessary nutrients for optimal exercise.
[0047] Alternatively, daily values 204 or target values can be
apportioned to individual meals. For example, instead of
calculating sufficiency values for an entire day, the user may
specify (or the system may automatically determine) that daily
values 204 or target values should be apportioned 30% to breakfast,
30% to lunch, and 40% to dinner. Thus, instead of the sufficiency
values calculated above, the system might calculate a breakfast
carbohydrate sufficiency value of 66.7%, a fat sufficiency value of
75%, and a protein sufficiency value of 166.7%. In some
embodiments, sufficiency values are capped at 100% instead. These
values can then be blended as described above for each meal to meet
the requirements of a broader timeline.
[0048] Micronutrient sufficiency scores 512 may be calculated next.
As described above with respect to macronutrients, the values for
the other nutrients (such as vitamins, minerals, water, fiber,
essential fatty acids, amino acids, and other nutrients that are
not macronutrients) provided by each potential meal can be
calculated compared against the target values for the respective
nutrients and blended as described above. In some embodiments, or
for some meals, micronutrient information may not be available. For
example, a restaurant may provide a macronutrient breakdown for
their meals, but not micronutrient content. In such cases, the
micronutrient sufficiency score 512 calculation step may be omitted
and a limited meal score presented to the user 302 that does not
include micronutrient information. As described above with respect
to macronutrients, micronutrient sufficiency score 512 may be
calculated for a day, an individual meal, or over a longer time
period such as a week or month.
[0049] Next, detriment values may be calculated. Broadly speaking,
detriment values can be assigned for any property of a meal that
makes it undesirable. For example, exceeding a target value for a
capped nutrient may cause a detriment value to be assigned. Thus,
for example, if a meal would exceed the target value for total
caloric input (for the day or for a particular meal), then a
detriment value may be assigned. As described above, some nutrients
(such as trans fats or added sugars) may have a target value of
zero, so that a meal including any of those nutrients will have an
associated detriment.
[0050] Continuing with the exemplary embodiment depicted in FIG. 5,
detriment scores 514 may be calculated based on an overage amount
(for example, if a meal contains 127% of the target value for
saturated fat, it may be assigned a detriment of 27%) or a fixed
detriment per amount of the undesirable nutrient (for example, 1%
detriment for each gram of trans fats). For example, in the
embodiment depicted in FIG. 5, 8 grams of saturated fats 516 are 3
grams over the recommended target value or limit of 5 gams. The
total detriment score 518 may be -3. The total detriment score 518
may also be represented as a percentage as described in the
macronutrients section above.
[0051] In embodiments, the overall score for the meal, or the meal
score 520, may be calculated and presented to the user 302. As with
the individual subscores calculated above, the macronutrient score
502, micronutrient score 512, and detriment scores 514 can be
aggregated in a variety of ways to arrive at a final meal score
520. For example, the detriment subscore can be subtracted from the
sum of the macronutrient and micronutrient subscores to determine
the final meal score 520. Alternatively, the sum of the
macronutrient score 502 and micronutrient scores 512 can be divided
by 100% plus the detriment score 516. Other aggregation metrics are
also contemplated as being within the scope of the invention. For
example, a dietician may provide a scoring algorithm or set of
scoring weights for an individual or for a life stage group that
can be used instead of the more broadly applicable calculations
described above. Once calculated, the final meal score 520 (alone
or in combination with the component subscores) can be displayed to
the user 302 via the GUI 500. In some embodiments, the user 302 can
mark one of the potential meals as chosen (i.e., indicate what they
have eaten) to allow the system to adjust target values to reflect
what the user has consumed. In yet other embodiments, the system
may present meals based on future exercise or activity that the
user 302 may have stored in a calendar or a stored record of the
user 302 typical activities and preferences.
[0052] In an exemplary embodiment depicted in FIG. 6, the user 302
may have embodiments of the invention accessible on a mobile device
602 such as a phone, tablet, watch, or any other mobile device 602
that may contain the functionality to operate the GUI. The system
may process information online anywhere that Wi-Fi or satellite
reception is available or may access an internally stored database.
For example, the system may be used in a restaurant.
[0053] As depicted in FIG. 6 the user 302 may use the system GUI
600 in conjunction with the mobile device 602 functionality such as
a camera or video to image a meal. The system may have image
recognition technology and access either a mobile device 602 stored
database or an online database to process the image data and
determine the image that has been captured by the mobile device
602. It is determined that the image is of pepperoni pizza. Once
confirmed by the user 302 that the image is correctly recognized,
the image may be stored in the database for future food
recognition. The food and ingredients may also be input manually or
selected from possible images as the system may provide multiple
options if the image recognition software finds multiple similar
images.
[0054] In some embodiments, the user specifies one or more
potential meals. In other embodiments, potential meals can be
automatically recognized by, for example, using machine-learning
techniques to recognize a picture of the potential meal captured by
the user. In still other embodiments, potential meals can be
recognized by performing text recognition on a menu, by downloading
a digital restaurant menu, or by scanning a barcode associated with
a pre-packaged meal. The system may access the mobile device 602
GPS position and determine that the user 302 is at a restaurant and
narrow the image searching based on the location. Broadly speaking,
any technique for recognizing a potential meal is contemplated as
being within the scope of the invention. Further, any hardware or
software that may provide information to any condition of the user
302 that may adjust the nutrient plan 324 dynamically and any
hardware or software that may order the food containing the
nutrients provided in the nutrient plan 324 may be connected to and
implemented by the system.
[0055] As depicted in the exemplary embodiment depicted in FIG. 7,
the user 302 may also select an image provided by the system from
the restaurant's online website. For example, the user 302 may
enter a restaurant and the system may access a mobile device 602
GPS and determine that the user 302 has entered the restaurant. The
system may access the restaurant's online menu to compare the
images received from the mobile device 602 functions and provide a
calculated score of the food in the image. Alternatively, the
system may access the menu, calculate a score for each menu item
and send a list of suggestions along with the menu item scores.
[0056] Turning now to FIG. 7, depicting an exemplary embodiment of
a GUI 700 of the invention in which the image taken in the
embodiment depicted in FIG. 6 is uploaded for evaluation by the
system. On the GUI 700 is a user 302 name Victoria and the date
702. The date 702 is listed as any interactions and food consumed
or imaged may be stored and associated with the date 702. Each meal
may be automatically or manually saved on a calendar for each date
702 for tracking by the user 302 or the system. The system may use
this information to build user 302 tendencies or score meals based
on future expected user 302 activity.
[0057] The user activity 704 and steps and calories burned 706 for
the day may also be displayed. This may also be activity for the
week or month as, in embodiments, the GUI 700 may be customizable.
The activity 704 may be entered manually by the user 302 or may be
accessed from a peripheral device such as an activity tracker like
a watch, wrist band, mobile phone, elliptical or any other device
that the user 302 may wear or user that may track steps, heart
rate, or any other movement that may be used to monitor activity.
Information from exercise machines may also be received, displayed,
and used to calculate activity 704, calories burned 706, and
nutrient needed information, detriment, and recommended food scores
710. The activity 704 information may be retrieved through wired or
wireless communication. The recommended score 710 may be a minimum
score and a maximum score may be set at, for example, 100.
[0058] The user 302 medical information may also be used by the
system. The medical information in the embodiment depicted in FIG.
7 is the user glucose levels 708. The glucose levels 708 may be
accessed from a glucose monitor worn by the user 302. The glucose
levels 708 may also be input manually. Other medical information
such as cardiovascular information, blood pressure, temperature,
DNA genome, microbiome-specific data, known or suspected allergies,
or any other medical information that may be associated with a
medical condition of the user 302 may be used.
[0059] Meal associated information 712 may display the image of the
meal that is chosen by the user 302 for the system to determine the
score 65 or the meal associated information 712 may display a meal
suggested to the user by the system. The suggestion may come from
an online website for the restaurant. In the embodiment, the user
has imaged the meal and the image recognition software has
determined that the imaged meal is pepperoni pizza from Roy's
Italian Grill 714. The determination of the imaged food may be from
the image recognition software only or may be a combination of the
user's location drawn from a mobile device and image recognition
software as described above. The GUI 700 may also present the
scoring characteristics to the user 302. The meal macronutrients
716, vitamins and minerals 718, and detriments 720 may be
presented. The overall score 722 for the meal or a recommendation
that gives a score 722 within the recommended range may also be
presented to the user. The score 722 may be based on the
macronutrients 716, micronutrients 718, and the detriments 720 as
described above. The user 302 may confirm 724 that the image is
correct and may also confirm that the meal is the one selected and
consumed by the user 302. The information may be updated in the
user's 302 meal calendar manually or automatically.
[0060] The user 302 may also be presented with a further breakdown
of the meal as depicted in FIGS. 8 and 9. FIGS. 8 and 9 present a
representative GUI 800 of an embodiment of the invention displaying
Allergens 802 and Macronutrients 804. The presentation options are
not limited and may provide the user with any information about the
meal.
[0061] The Allergens 802 section may display the known allergens
802 in the meal. The meal of the embodiment contains dairy, fish,
and possibly egg. If the user 302 is allergic to eggs then this
alerts the user 302 that the user 302 may inquire further as to
whether egg is in the meal. If the user 302 is lactose intolerant
then the user 302 may choose other options or see if the restaurant
has replacements. All the fields of the GUI 800 are manually
customizable and may be updated by the user 302. For example, if
dairy is removed from the meal, the user 302 may update the GUI 800
and the corresponding nutrients and scores may update automatically
or manually.
[0062] The next section presents the macronutrients 804. Calories
806, fat 808, carbohydrates 810, sodium 812, protein 814, and
dietary fiber 816 are displayed, but any macronutrients 804
contained within the meal may be displayed. The amounts 818 and
scores (not shown) for each of the macronutrients 804 for a given
meal or at any given time based on the dynamically updated user
profile may also be presented via the GUI 800.
[0063] Turning to the continuing embodiment depicted in FIG. 9, the
list of vitamins and minerals 902 may also be presented in the meal
breakdown. In the embodiment, Vitamin A 904, Vitamin C 906, and
Iron 908 are provided by the meal. In embodiments, the list of
vitamins and minerals 902 may also provide the amounts of the
vitamins and minerals 902 as in the previous macronutrients 804
section. In embodiments, the detriments may also be presented in
the meal breakdown. The scores for each of the micronutrients and
detriments for a given meal or at any given time based on the
dynamically updated user profile may also be presented.
[0064] Another section in the meal breakdown may be Tags 910. The
Tags may be a list of ingredients or components to a meal. The list
of ingredients may be accessed from a stored or online database or
may be from the restaurant's online menu. The macronutrients 804
and vitamins and minerals 902 list may be taken from the components
in the Tags 910 section. The user 302 may add or delete any Tags
910 as the meal is changed. The user 302 may select each ingredient
or component and be presented a further breakdown of the nutrients
and detriments in each ingredient. This may provide the user 302
with further information for better selections. For example, after
selecting and looking through the ingredients, the user may see
that parmesan 912 provides high calories to the dish. The user 302
may decide that parmesan 912 is not worth the number of calories
and elect to have this ingredient excluded from the dish. The user
302 may then remove the ingredient from the list and the scores may
be adjusted accordingly.
[0065] The user 302 may be presented the meal breakdown to make an
informed decision or to review past meals from the user 302 meal
calendar to make more informed decisions in the future. For
example, the user 302 may select a meal with broccoli however upon
review of the calendar and the recommended nutrients it is seen
that the nutrients provided by broccoli are in abundance and the
vegetable should be substituted for a fruit based on user 302
planned future activity that the system does not have stored. The
user proceeds to substitute an apple and the daily nutritional
value changes.
[0066] Turning now to an exemplary embodiment depicted in FIG. 10.
The GUI 1000 may connect the user 302 with online meal plans. An
exemplary company named Online Meals 1002 may deliver full meals to
the user 302. The meals may be selected based on the dietary
restrictions of the user 302 and the score 1004 provided to each
meal by the system. The system may score 1004 each meal and
recommend meals based on the scores 1004 and dietary restrictions.
As depicted the Herb-Grilled Salmon 1006 has been given a score
1004 of 90%. Further, the GUI may present the breakdown of the meal
as shown in FIGS. 8 and 9. The GUI may provide functionality for
selecting and purchasing the meals through the website or a
downloaded application for Online Meals 1002.
[0067] Turning now to an exemplary embodiment of a smart kitchen
1100 depicted in FIG. 11. The Online Meals 1002 purchased in the
previous embodiment and other groceries may be stored in a smart
refrigerator 1102. The meals and ingredients in the refrigerator
1102 may be stored in the refrigerator memory and may be accessed
remotely by a mobile device 1104. The system may be stored on or
accessed through the refrigerator 1102 and may provide meal
recommendations based on the ingredients and nutrients in the meals
in the refrigerator 1102. The meals and ingredients selected by the
user may also be input into the system via the refrigerator 1102
and the system updated with the information to provide new nutrient
recommendation scores for all possible meals in the refrigerator
1102 dynamically based on user 302 activity, diet information, and
preferences.
[0068] Continuing with the exemplary embodiment depicted in FIG.
11, the system may be connected to any kitchen smart appliance such
as an oven 1106, microwave 1108, blender 1110, a smart television
(not shown), or any other type of kitchen or non-kitchen appliance
or electronics that may access the internet. For example, a
treadmill 1112 may send information related to a user 302 exercise
routine. The system may then access the refrigerator 1102
ingredients and recommend a high protein meal. The user 302 may
customize the system content such that when an exercise such as
using the treadmill 1112, or jogging, is performed the system
provides shake options. The options may be provided based on the
contents of the refrigerator 1102 and further based on a diet that
the user 302 is on. Once the exercise is finished, the user 302 may
access the GUI 1100 on a laptop computer 1114, or mobile device
1104 such as a smartphone, or the refrigerator 1102 and view the
recommendations. The GUI 800 may display an option for a strawberry
banana shake with kale. The shake has been given a score of 75 and
is not only based on the subscores for macronutrients,
micronutrients, and detriments, but may also be based on a recorded
history of the user's 302 choices. This may provide the user 302
with selections that the user 302 prefers. The user 302 may also
rate the meals and shakes such that the system may "learn" what the
user 302 prefers and include this in the recommendations. The user
recommendations, ratings, and preferences may be stored for
restaurants as well, and may be applicable to any embodiments of
the system.
[0069] The system content may be accessed through all appliances,
activity trackers, mobile devices 1114, or any intelligent personal
assistant hardware such as a mobile personal assistant (e.g.,
Apple.RTM. HomePod, Google.RTM. Assistant, or Amazon.RTM. Echo) or,
for example, an online voice activated device 1116. The online
voice activated device 1116 may be used to update or customize the
system. For example, the user 302 may select a meal from the
refrigerator 1102 and the system may be automatically updated and
the list of ingredients on a grocery list stored on the online
voice activated device 1116 may be updated based on the nutrients
that the user 302 has consumed. The user 302 may also connect any
list from the online voice activated device 1116 such that the user
302 may speak to the device and the list may be updated
accordingly.
[0070] The grocery list stored on the system may also be connected
to a grocery store online system and the list may be sent to the
grocery store for curb side pick-up or a grocery shopping plan may
be created based on the location of the list items within the
grocery store. The system may be connected to any smart carts or
aisles in the grocery store and may be accessible to the user 302
while shopping. Notifications or alerts may be sent to the user via
the carts or displays in the aisles or via any personal mobile
device of the user 302 when the user 302 is close to a list item
within the store. The system may either alert or order any food
item that may be on the grocery list as determined by the nutrient
plan 324. Alternatively, data provided by such smart carts may be
used to provide nutrient information, ingredient information, or to
suggest meals to the user.
[0071] The system may also send information to the online voice
activated device 1116 automatically. Recommended meals,
ingredients, sufficiency or detriment scores, or the user nutrient
or medical information may be provided to the user 302 via the
online voice activated device 1116. For example, the user's 302
glucose levels may be low. The system may recognize the low glucose
levels on the glucometer 1118 that may be attached to the user 302
and alert the user 302 via the online voice activated device 1116
automatically with meal recommendations such as a snack to reduce
the glucose levels. In other embodiments, the user 302 may exercise
on the treadmill 1112 as described above and the voice activated
device 1116 may provide meal, shake, or snack recommendations as
supplied via the system based on the exercise and the refrigerator
1102 contents. The recommendations may also be supplied to the user
302 via any embodiment of the GUI 1100 on any one of the mobile
devices 1104, appliances, or computers described above. The system
may connect with any devices in the smart kitchen 1100 and may be
wired, wireless or connect over a network 1120.
[0072] Data from body worn peripheral devices such as the
glucometer 1118, and the mobile devices 1104 may be used in any
embodiment of the invention. For example, if a user 302 has a
fitness band that tracks their activity level, then the total
caloric intake for the day can be adjusted based on how much energy
the user 302 has expended. Similarly, if the user's 302 blood
pressure is elevated, then the recommended intake of sodium can be
reduced. Any biometric data can be used to adjust the target
values. For example, if the user is diabetic and monitors their
blood sugar levels periodically or continuously, then the target
values for simplex and complex carbohydrates can be adjusted on the
fly to maintain an optimal blood sugar level. Galvanic skin
response can be used to determine the user's hydration level, which
can in turn be used to adjust the target value for water.
Respiration rate and history, perspiration, body temperature, or
any other biometric measurement, now known or later developed, can
also be used to adjust the dynamic user profile.
[0073] Turning now to the exemplary GUI 1200 depicted in FIG. 12.
The system may access the information stored on the many peripheral
devices and the smart kitchen appliances as described above. The
exemplary embodiment in FIG. 12 depicts the GUI 1200 presenting
access to the kitchen smart appliances of FIG. 11. The appliances
1202 may automatically be accessible since they may be in wireless
communication. The user 302 may select an appliance 1202 then
proceed to view the food that may be available within the appliance
1202. For example, the refrigerator may be selected and the online
meals section may be selected beyond that. The user may select
Herb-Grilled Salmon and the system provides the score for the
Herb-Grilled Salmon.
[0074] The user 302 may also manage the appliances 1202 from the
GUI 1200. For example, the user may place ingredients for a shake
in the blender 1110. The user 302 may then exercise. The mobile
device 1104 may recognize that the user is finished with the
exercise and automatically send a signal via the system to start
the blender 1110 and prepare the shake. Alternatively, the user 302
may arrive home from work and a sensor on the door alerts the
system that the user 302 is home. The daily activity for the user
has been recorded and the nutrient sufficiency scores are known.
The system may score the items in the refrigerator 1102 and may
alert the online voice activated device 1118. As the user 302
enters, the online voice activated device 1118 may alert the user
302 as to what is for dinner as well as provide the ingredients and
the sufficiency scores. The settings may be stored on the devices
and input via the GUI 1200.
[0075] The system may also calculate the score for all ingredients
1206 that may be present in an appliance 1204 and provide the user
with scores and meal or snack recommendations 1208. For example,
the system may be presented with Spicy Ahi Tuna Salad and
Herb-Grilled Salmon from the Online Meals 1210 section in the GUI
1200. The Spicy Ahi Tuna Salad may have a score of 74 while the
Herb-Grilled Salmon has a score 1212 of 90. The system then may
recommend the meal with the higher score, i.e. the Herb-Grilled
Salmon.
[0076] Turning now to an exemplary GUI 1300 depicted in FIG. 13.
The system may provide two meal options that have high sufficiency
scores; the Herb-Grilled Salmon 1302 with a score of 90% 1304 and
the Spicy Ahi Tuna Salad 1306 with a score of 74% 1308. The system
may provide scores for meals based on demographic data, biometric
data, exercise, and any other data associated with the user 302,
but, in embodiments, the system may also provide scores based on
future data. For example, the GUI 1300 may be providing meal
options for lunch on Wednesday. The system, through
machine-learning, neural networks, or statistical algorithm, may
provide a probability that the user 302 will exercise on Wednesday
afternoon. This may be calculated from history or a schedule such
as a calendar. It also may be determined that with a certain
probability the user 302 may do a particular exercise such as
jogging. The expected calories burned and nutrients that may need
replenishing may also be predicted. The meals recommended for lunch
may be based on past information but also expected future
activities. This future prediction may help the user 302 stay
healthy and meet goals.
[0077] Turning now to an embodiment depicted in FIG. 14 of a GUI
1400 presenting the nutrient breakdown for the Herb-Grilled Salmon
1402. The breakdown may include macronutrient sufficiency score
1404 of 81%. A Vitamins and Minerals score 1406 of 74% and a
Detriments score 1408 of 94%. Each score may also provide an
explanation of the score such that the user 302 may more easily
follow the scoring and track meals. The score breakdown may also be
provided in a pinwheel manner as displayed in the lower section
1410. This visual may make it easier for the user to instantly
understand the structure. In embodiments, the scores may be
displayed in a bar graph, line graph, or any way that may be easily
understandable to the user 302. The system may also track changes
and all histories of the user health and scores and may be
presented to the user in any manner that may be easily understood.
In embodiments, the system may track health history from on online
database and may update health information such that it may be
accessible and edited by a health practitioner.
[0078] Turning now to FIG. 15. A flowchart illustrating the
operation of a method in accordance with embodiments of the
invention is depicted and referred to generally by reference
numeral 1500. The method begins at step 1502, where a baseline
nutrient profile for a user is constructed. The baseline nutrient
profile may be a starting point for all users that may be generally
constructed from a standard nutrient chart as provided by, for
example, the United States Food and Drug Administration.
[0079] Once the baseline nutrient profile for the user has been
constructed, processing can proceed to step 1504, where the
baseline nutrient profile is adjusted based on user demographic
data to create the custom user profile. The nutrient profile may be
adjusted based on a user's height, weight, age, sex, diet, goals,
genetics, or any other user characteristic that may influence the
kind of nutrients or the amount of nutrients to be consumed by the
user.
[0080] In some embodiments, processing can then proceed to step
1506, where the custom user profile can be dynamically adjusted
based on user biometrics to form the dynamic user profile. The
dynamic adjustment may be caused by nutrient intake, user activity,
medical procedures, medical practitioner input, or any other input
that may influence the recommended nutrient intake of the user. The
system may receive the inputs manually or automatically through an
activity tracker such as a watch, wristband, mobile device,
treadmill, elliptical or any other device that may monitor
activity, or health monitor such as a glucometer, blood pressure
meter, galvanometer, or any other device that may be used to track
the user's health.
[0081] Processing can then proceed to loop 1508, where steps 1510
through 1530 are repeated for each potential meal to be scored. The
potential meals may be provided by the user or automatically
retrieved online. The potential meals may be based on history or
future expected activity by the user. The potential meals may also
be provided by a restaurant, stored in a user's kitchen, or
provided as a recommendation based on the user preferences or
tracked history calculated probability of the user's actions.
[0082] For each potential meal, loop 1508 begins with decision
1510, where it is determined whether each food making up the meal
is stored in the food database. If so, processing proceeds to step
1512; otherwise, processing proceeds instead to step 1514. At step
1512, nutrient information for the food is retrieved from the food
database. Broadly speaking, the food database allows certain foods
to be stored as a whole without the need to score individual
ingredients. In some embodiments, restaurant meals are stored in
the food database based on published nutrition information.
Homemade foods that the user has previously prepared may also be
stored in the food database to remove the need for the user to
re-enter food details. If the food is not stored in the food
database, processing proceeds to step 1514, where the user can
enter ingredient information for the food or the system may access
online information about the possible food such as online menus and
recipes.
[0083] From step 1512 or step 1514, processing proceeds to step
1516, where meals are scaled and combined. In embodiments, any of
the components of a meal may be measured or scaled and combined
with the other components of the meal to create a combined meal
score.
[0084] Once the aggregate nutrient information has been determined
for each meal, the meal can be scored. This process begins at step
1518, where the macronutrient sufficiency score is calculated. In
some embodiments, subscores are first generated for each nutrient.
Macronutrient sufficiency values may be calculated for a
recommended daily nutrition plan and may be broken into meals and
snacks or into any manner that may be preferred by the user.
[0085] Processing can then proceed to step 1520, where
micronutrient sufficiency scores can be calculated. The
micronutrient score may be calculated similarly to the
macronutrient score.
[0086] Next, processing continues to step 1522, where detriment
values are calculated. Detriment values may be assigned to any meal
or ingredient that may make it undesirable such as exceeding a
target value or having little to no need in the recommended daily
nutrition plan.
[0087] Processing can then proceed to a step 1524, where the
overall score for the meal is calculated and presented to the user.
As with the individual subscores calculated above, the
macronutrient, micronutrient, and detriment scores can be
aggregated in a variety of ways to arrive at a final meal score.
Combining the ingredients into a combined meal score may simplify
the process reduce the amount of time the user may spend tending to
the diet.
[0088] Processing can then proceed to a step 1526, where the system
may retrieve saved user preferences. The user preferences may help
determine meals or snacks to recommend. In some embodiments, the
meals may be based on user activity preferences.
[0089] Processing can then proceed to step 1528, where the system
may recommend selected high scoring meals from a plurality of
potential meals. The potential meals may be gather from an online
menu or a grocery list in the user's home.
[0090] Processing can then proceed to step 1530, where the user
profile and recommended daily nutrition plan is dynamically updated
with the user selection. As the user makes a selection or edits any
part of the daily nutrition plan the user profile and daily
nutrition plan may automatically or manually update
accordingly.
[0091] Any of the above steps of the exemplary flow chart 1500
depicted in FIG. 15 may be moved or omitted. For example, if the
user is at a restaurant and presenting one meal option to the
system for evaluation step 1528 may be omitted as the system does
not provide recommendations based on a plurality of potential
meals.
[0092] Any sections of any embodiment of a graphical user interface
may be rearranged and may be customizable in any way. Any section
may be omitted or added and any section may be rearranged with any
other section or sections.
[0093] Many different arrangements of the various components
depicted, as well as components not shown, are possible without
departing from the scope of the claims below. Embodiments of the
invention have been described with the intent to be illustrative
rather than restrictive. Alternative embodiments will become
apparent to readers of this disclosure after and because of reading
it. Alternative means of implementing the aforementioned can be
completed without departing from the scope of the claims below.
Certain features and subcombinations are of utility and may be
employed without reference to other features and subcombinations
and are contemplated within the scope of the claims. Although the
invention has been described with reference to the embodiments
illustrated in the attached drawing figures, it is noted that
equivalents may be employed and substitutions made herein without
departing from the scope of the invention as recited in the
claims.
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